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Research Collection School Of Computing and Information Systems

2003

Artificial Intelligence and Robotics

Articles 1 - 8 of 8

Full-Text Articles in Physical Sciences and Mathematics

Predicting Nonlinear Network Traffic Using Fuzzy Neural Network, Zhaoxia Wang, Tingzhu Hao, Zengqiang Chen, Zhuzhi Yuan Dec 2003

Predicting Nonlinear Network Traffic Using Fuzzy Neural Network, Zhaoxia Wang, Tingzhu Hao, Zengqiang Chen, Zhuzhi Yuan

Research Collection School Of Computing and Information Systems

Network traffic is a complex and nonlinear process, which is significantly affected by immeasurable parameters and variables. This paper addresses the use of the five-layer fuzzy neural network (FNN) for predicting the nonlinear network traffic. The structure of this system is introduced in detail. Through training the FNN using back-propagation algorithm with inertia] terms the traffic series can be well predicted by this FNN system. We analyze the performance of the FNN in terms of prediction ability as compared with solely neural network. The simulation demonstrates that the proposed FNN is superior to the solely neural network systems. In addition, …

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Task Allocation Via Multi-Agent Coalition Formation: Taxonomy, Algorithms And Complexity, Hoong Chuin Lau, L. Zhang Nov 2003

Task Allocation Via Multi-Agent Coalition Formation: Taxonomy, Algorithms And Complexity, Hoong Chuin Lau, L. Zhang

Research Collection School Of Computing and Information Systems

Coalition formation has become a key topic in multiagent research. In this paper, we propose a preliminary classification for the coalition formation problem based on three driving factors (demands, resources and profit objectives). We divide our analysis into 5 cases. For each case, we present algorithms and complexity results. We anticipate that with future research, this classification can be extended in similar fashion to the comprehensive classification for the job scheduling problem.

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Safe Robot Driving In Cluttered Environments, Chuck Thorpe, Justin Carlson, Dave Duggins, Jay Gowdy, Rob Maclachlan, Christoph Mertz, Arne Suppe, Bob Wang Oct 2003

Safe Robot Driving In Cluttered Environments, Chuck Thorpe, Justin Carlson, Dave Duggins, Jay Gowdy, Rob Maclachlan, Christoph Mertz, Arne Suppe, Bob Wang

Research Collection School Of Computing and Information Systems

The Navlab group at Carnegie Mellon University has a long history of development of automated vehicles and intelligent systems for driver assistance. The earlier work of the group concentrated on road following, cross-country driving, and obstacle detection. The new focus is on short-range sensing, to look all around the vehicle for safe driving. The current system uses video sensing, laser rangefinders, a novel light-stripe rangefinder, software to process each sensor individually, and a map-based fusion system. The complete system has been demonstrated on the Navlab 11 vehicle for monitoring the environment of a vehicle driving through a cluttered urban environment, …

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Multi-Agent Coalition Via Autonomous Price Negotiation In A Real-Time Web Environment, Hoong Chuin Lau, Wei Sian Lim Oct 2003

Multi-Agent Coalition Via Autonomous Price Negotiation In A Real-Time Web Environment, Hoong Chuin Lau, Wei Sian Lim

Research Collection School Of Computing and Information Systems

In e-marketplaces, customers specify job requests in real-time and agents form coalitions to service them. This paper proposes a protocol for self-interested agents to negotiate prices in forming successful coalitions. We propose and experiment with two negotiation schemes: one allows information sharing while the other does not.

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Solving Multi-Objective Multi-Constrained Optimization Problems Using Hybrid Ants System And Tabu Search, Hoong Chuin Lau, Min Kwang Lim, Wee Chong Wan, Hui Wang, Xiaotao Wu Aug 2003

Solving Multi-Objective Multi-Constrained Optimization Problems Using Hybrid Ants System And Tabu Search, Hoong Chuin Lau, Min Kwang Lim, Wee Chong Wan, Hui Wang, Xiaotao Wu

Research Collection School Of Computing and Information Systems

Many real-world optimization problems today are multi-objective multi-constraint generalizations of NP-hard problems. A classic case we study in this paper is the Inventory Routing Problem with Time Windows (IRPTW). IRPTW considers inventory costs across multiple instances of Vehicle Routing Problem with Time Windows (VRPTW). The latter is in turn extended with time-windows constraints from the Vehicle Routing Problem (VRP), which is extended with optimal fleet size objective from the single-objective Traveling Salesman Problem (TSP). While single-objective problems like TSP are solved effectively using meta-heuristics, it is not obvious how to cope with the increasing complexity systematically as the problem is …

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A Generic Object-Oriented Tabu Search Framework, Hoong Chuin Lau, Wee Chong Wan, Xiaomin Jia Aug 2003

A Generic Object-Oriented Tabu Search Framework, Hoong Chuin Lau, Wee Chong Wan, Xiaomin Jia

Research Collection School Of Computing and Information Systems

Presently, most tabu search designers devise their applications without considering the potential of design and code reuse, which consequently prolong the development of subsequent applications. In this paper, we propose a software solution known as Tabu Search Framework (TSF), which is a generic C++ software framework for tabu search implementation. The framework excels in code recycling through the use of a welldesigned set of generic abstract classes that clearly define their collaborative roles in the algorithm. Additionally, the framework incorporates a centralized process and control mechanism that enhances the search with intelligence. This results in a generic framework that is …

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A Generic Object-Oriented Tabu Search Framework, Hoong Chuin Lau Jul 2003

A Generic Object-Oriented Tabu Search Framework, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Presently, most tabu search designers devise their applications without considering the potential of design and code reuse, which consequently prolong the development of subsequent applications. In this paper, we propose a software solution known as Tabu Search Framework (TSF), which is a generic C++ software framework for tabu search implementation. The framework excels in code recycling through the use of a welldesigned set of generic abstract classes that clearly define their collaborative roles in the algorithm. Additionally, the framework incorporates a centralized process and control mechanism that enhances the search with intelligence. This results in a generic framework that is …

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On Machine Learning Methods For Chinese Document Classification, Ji He, Ah-Hwee Tan, Chew-Lim Tan May 2003

On Machine Learning Methods For Chinese Document Classification, Ji He, Ah-Hwee Tan, Chew-Lim Tan

Research Collection School Of Computing and Information Systems

This paper reports our comparative evaluation of three machine learning methods, namely k Nearest Neighbor (kNN), Support Vector Machines (SVM), and Adaptive Resonance Associative Map (ARAM) for Chinese document categorization. Based on two Chinese corpora, a series of controlled experiments evaluated their learning capabilities and efficiency in mining text classification knowledge. Benchmark experiments showed that their predictive performance were roughly comparable, especially on clean and well organized data sets. While kNN and ARAM yield better performances than SVM on small and clean data sets, SVM and ARAM significantly outperformed kNN on noisy data. Comparing efficiency, kNN was notably more costly …

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